Nvidia CEO Jensen Huang addressed growing concerns about the skyrocketing costs of artificial intelligence (AI) computing during his keynote at the company’s annual developer conference on Tuesday. In a two-hour presentation at the highly anticipated GTC event in San Jose, Huang showcased new, more powerful chips and software that promise to make AI technologies more cost-efficient and profitable for customers.
Among the highlights was the introduction of Nvidia’s new flagship AI processor, the Blackwell Ultra, as well as a roadmap for future generations, including the Vera Rubin upgrade set for late 2026. Huang also revealed Dynamo, a suite of software designed to optimize AI hardware, calling it “the operating system of an AI factory.”
The GTC event, once a modest gathering for developers, has evolved into a major platform for Nvidia to present its technological advances, with global tech leaders and investors keenly watching the company’s every move. However, despite Huang’s unveiling of new hardware, software, and partnerships, Nvidia’s stock closed down more than 3% on Tuesday, reflecting investor apprehension.
Pushing the Boundaries of AI Technology
Nvidia, initially known for its computer gaming chips, has transformed into a critical player in multiple tech sectors, particularly AI. At the conference, Huang emphasized that the Blackwell Ultra processor would be available by the second half of 2025, with the Vera Rubin release following a year later. These advancements are part of Nvidia’s broader plan to lead the AI hardware race.
In addition to hardware, Huang introduced several strategic partnerships, including one with General Motors to integrate AI into next-gen vehicles, factories, and robots. The company is also working with Walt Disney Co. and Google’s DeepMind on the Isaac GR00T N1 platform to boost humanoid robot development.
Furthermore, Nvidia is collaborating with telecommunications giants like T-Mobile and Cisco to build AI-driven wireless hardware for future 6G networks, the successor to current 5G technology.
AI Spending Faces Scrutiny Amid Market Uncertainty
Despite the grand announcements, Nvidia’s stock has faced turbulence in 2025, with concerns about the sustainability of AI investments growing. Earlier this year, a claim from Chinese startup DeepSeek, which developed a competitive AI model using fewer resources, raised questions about the pace of AI infrastructure spending.
However, major Nvidia customers like Microsoft and Amazon’s AWS have committed to continuing AI investments throughout 2025, underscoring the ongoing demand for high-performance computing. A recent Bloomberg Intelligence report revealed that data center operators, including hyperscalers, are expected to spend $371 billion on AI facilities this year—up 44% from 2024.
Still, broader concerns about trade wars and potential economic recessions have cast a shadow over Nvidia’s stock performance. As of Tuesday, shares had fallen 14% this year, with Tuesday’s decline further exacerbated by news of Nvidia’s collaboration with General Motors, which negatively impacted the stock of self-driving technology company Mobileye.
Quantum and Photonics
Despite the market’s uncertain outlook, Huang presented an optimistic vision for Nvidia’s future, detailing plans for a new quantum computing research lab in Boston and innovations that blend silicon with photonics to revolutionize AI systems.
Nvidia’s journey is far from without challenges. The company has struggled with production delays and bottlenecks in its efforts to meet demand for its cutting-edge chips. While Nvidia has committed to ramping up production, the company has warned that these efforts could put pressure on profit margins in the short term.
As part of his update, Huang noted that top cloud vendors such as Amazon, Microsoft, Google, and Oracle had purchased 1.3 million of Nvidia’s older Hopper chips last year, with purchases of the newer Blackwell chips already reaching 3.6 million in 2025.
New Innovations on the Horizon
Looking ahead, Nvidia’s plans include the release of Vera Rubin’s successor, the Rubin Ultra, expected in late 2027. The company also teased a future chip generation, named Feynman, likely referencing the renowned physicist Richard Feynman, known for his contributions to quantum mechanics.
As Nvidia moves forward in its mission to transform the AI landscape, the company’s ability to navigate production challenges and capitalize on new technologies, such as quantum computing and photonics, will be pivotal in securing its position as a leader in the evolving AI industry.
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